文件名称:8a84c82850579e3a5e0d221bf92f63b1ffd5
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- 2017-01-20
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The Bee Colony Optimization (BCO) meta-heuristic deals with combinatorial optimization problems. It is
biologically inspired method that explores collective intelligence applied by the honey bees during nectar
collecting process. In this paper we perform empirical study of the BCO algorithm. We apply BCO to opti-
mize numerous numerical test functions. The obtained results are compared with the results in the liter-
ature. The numerical experiments performed on well-known benchmark functions show that the BCO is
competitive with other methods and it can generate high-quality solutions within negligible CPU times
biologically inspired method that explores collective intelligence applied by the honey bees during nectar
collecting process. In this paper we perform empirical study of the BCO algorithm. We apply BCO to opti-
mize numerous numerical test functions. The obtained results are compared with the results in the liter-
ature. The numerical experiments performed on well-known benchmark functions show that the BCO is
competitive with other methods and it can generate high-quality solutions within negligible CPU times
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